Context

As of March 23 2021, there are 123 million confirmed COVID-19 cases and 2.7 million deaths reported to WHO for the 194 Member States.

COVID-19 mortality is an incomplete picture

• There are significant differences in how COVID deaths are reported between countries (https://observatoryihr.org/news/chinarussia-brazil-and-the-underreporting-of-covid19-cases)

  • Variations in testing access, diagnostic capacity and how COVID deaths are defined

  • Deaths may be misattributed to COVID-19 and, converse

• Excess mortality provides an estimate of the additional number of deaths for specified location and time period, compared to the number of deaths expected (often estimated using the same time period in the preceding year or averaged over several preceding years).

  • encompasses deaths from all causes

  • gives a summary measure of the ‘whole system’ impact.

Example

Regions

Ratio of excess to COVID-19

Modeling scaling factors for excess

Predicting country excess

Predicting country excess (ctd)

Mapping mean predicted excess mortality

Regional numbers of excess mortality

Overall for the year 2020:

• Global: 1.87 million COVID-19 and 3.75 million estimated excess deaths (UI 3.23-4.28)

  • AFRO: 45 thousand COVID-19 and 196 thousand estimated excess deaths (UI 114-278)

  • EMRO: 122 thousand COVID-19 and 320 thousand estimated excess deaths (UI 281-360)

  • EURO: 602 thousand COVID-19 and 1.1 million estimated excess deaths (UI 1.1-1.11)

  • PAHO: 896 thousand COVID-19 and 1.31 million estimated excess deaths (UI 1.29-1.32)

  • SEARO: 186 thousand COVID-19 and 638 thousand estimated excess deaths (UI 454-825)

  • WPRO: 20 thousand COVID-19 and 191 thousand estimated excess deaths (UI -14-399)

Barplots of regional excess deaths

Barplots of regional excess death-rates

Discussion (To Do)

• Countries (and data sources) that can be used to estimate excess mortality directly (Tier 1),

  • completeness, timeliness

• Approaches to indirectly estimate excess mortality using alternative data sources or models (Tier 2)

  • Corrections for incompleteness,
  • standardization and harmonization to extend usability.

• The most appropriate statistical models to estimate excess mortality in countries for which it cannot be determined empirically, directly or indirectly) (Tier 3). Considerations for the variable of interest, statistical model functional forms, best predictors/covariates. (Tier 3)

  • functional form eg \(\frac{d^o - d^e}{covid}\) vs \(\frac{d^o}{d^e + covid}\)

  • covariates eg historical NCD/COMM rates, age-patterns, population density, income, policies

  • Propagate uncertainty from background model